How To Retrieve The First Row Meeting Conditions In Pandas?
We are given a DataFrame in Pandas and need to retrieve the first row that meets certain conditions. In this article, we will explore all the possible approaches to retrieve the first-row meeting conditions in pandas.
Retrieve the First Row Meeting Conditions in Pandas
- Using loc function
- Using query function
- Using Boolean Indexing
Retrieve The First Row Meeting Conditions In Pandas Using loc function
In this example, we are using the loc method to filter rows where the score column is greater than 80, and then selecting the first row from the filtered DataFrame using iloc[0].
import pandas as pd
df = pd.DataFrame({
'name': ['w3wiki', 'CodingForAll', 'CodeWars'],
'score': [85, 90, 78],
'city': ['Noida', 'San Francisco', 'Los Angeles']
})
first_row = df.loc[df['score'] > 80].iloc[0]
print(first_row)
Output
name w3wiki score 85 city Noida Name: 0, dtype: object
Retrieve The First Row Meeting Conditions In Pandas Using query function
In this example, we are using the query method to filter rows where the score is greater than 80, and then retrieving the first row from the filtered results using iloc[0].
import pandas as pd
df = pd.DataFrame({
'name': ['w3wiki', 'CodingForAll', 'CodeWars'],
'score': [85, 90, 78],
'city': ['Noida', 'San Francisco', 'Los Angeles']
})
first_row = df.query('score > 80').iloc[0]
print(first_row)
Output
name w3wiki score 85 city Noida Name: 0, dtype: object
Retrieve The First Row Meeting Conditions In Pandas Using Boolean Indexing
In this example, we are using boolean indexing to filter rows where the score is greater than 80, and then using head(1) to get the first row, followed by iloc[0] to access it.
import pandas as pd
df = pd.DataFrame({
'name': ['w3wiki', 'CodingForAll', 'CodeWars'],
'score': [85, 90, 78],
'city': ['Noida', 'San Francisco', 'Los Angeles']
})
first_row = df[df['score'] > 80].head(1).iloc[0]
print(first_row)
Output
name w3wiki score 85 city Noida Name: 0, dtype: object
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